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Inverse Filter (inverse + filter)

Distribution by Scientific Domains

Earth and Environmental Science	100%

Selected Abstracts

Array-conditioned deconvolution of multiple-component teleseismic recordings

GEOPHYSICAL JOURNAL INTERNATIONAL, Issue 2 2010
C.-W. Chen
SUMMARY We investigate the applicability of an array-conditioned deconvolution technique, developed for analysing borehole seismic exploration data, to teleseismic receiver functions and data pre-processing steps for scattered wavefield imaging. This multichannel deconvolution technique constructs an approximate inverse filter to the estimated source signature by solving an overdetermined set of deconvolution equations, using an array of receivers detecting a common source. We find that this technique improves the efficiency and automation of receiver function calculation and data pre-processing workflow. We apply this technique to synthetic experiments and to teleseismic data recorded in a dense array in northern Canada. Our results show that this optimal deconvolution automatically determines and subsequently attenuates the noise from data, enhancing P -to- S converted phases in seismograms with various noise levels. In this context, the array-conditioned deconvolution presents a new, effective and automatic means for processing large amounts of array data, as it does not require any ad-hoc regularization; the regularization is achieved naturally by using the noise present in the array itself. [source]

Estimation of an optimal mixed-phase inverse filter

GEOPHYSICAL PROSPECTING, Issue 4 2000
Bjorn Ursin
Inverse filtering is applied to seismic data to remove the effect of the wavelet and to obtain an estimate of the reflectivity series. In many cases the wavelet is not known, and only an estimate of its autocorrelation function (ACF) can be computed. Solving the Yule-Walker equations gives the inverse filter which corresponds to a minimum-delay wavelet. When the wavelet is mixed delay, this inverse filter produces a poor result. By solving the extended Yule-Walker equations with the ACF of lag , on the main diagonal of the filter equations, it is possible to decompose the inverse filter into a finite-length filter convolved with an infinite-length filter. In a previous paper we proposed a mixed-delay inverse filter where the finite-length filter is maximum delay and the infinite-length filter is minimum delay. Here, we refine this technique by analysing the roots of the Z -transform polynomial of the finite-length filter. By varying the number of roots which are placed inside the unit circle of the mixed-delay inverse filter, at most 2, different filters are obtained. Applying each filter to a small data set (say a CMP gather), we choose the optimal filter to be the one for which the output has the largest Lp -norm, with p=5. This is done for increasing values of , to obtain a final optimal filter. From this optimal filter it is easy to construct the inverse wavelet which may be used as an estimate of the seismic wavelet. The new procedure has been applied to a synthetic wavelet and to an airgun wavelet to test its performance, and also to verify that the reconstructed wavelet is close to the original wavelet. The algorithm has also been applied to prestack marine seismic data, resulting in an improved stacked section compared with the one obtained by using a minimum-delay filter. [source]